Datapoints: A blog from the Lippincott Library of the Wharton School of Businesshttps://lippincottlibrary.wordpress.com
Wed, 24 Jun 2015 21:02:38 +0000enhourly1http://wordpress.com/https://s2.wp.com/i/buttonw-com.pngDatapoints: A blog from the Lippincott Library of the Wharton School of Businesshttps://lippincottlibrary.wordpress.com
Lippincott Library Seminar Room Constructionhttps://lippincottlibrary.wordpress.com/2015/06/13/lippincott-library-seminar-room-construction/
https://lippincottlibrary.wordpress.com/2015/06/13/lippincott-library-seminar-room-construction/#commentsSat, 13 Jun 2015 18:12:29 +0000http://lippincottlibrary.wordpress.com/?p=2393Continue reading →]]>If you have visited Lippincott Library in the past few weeks, you have undoubtedly noticed some major changes. As you enter the library, you will immediately encounter the “great wall of Lippincott” – a large barrier that has been constructed around what was once our reference and reserve services desk.

Thanks to the generosity of the Snyder family, we are building a 28-seat seminar room this summer. The new room will be located just inside Lippincott’s main entrance. It will have a flexible furniture configuration, allowing it to be used seminar-style, lecture-style or to be set up for smaller groups. This project also gives us the opportunity to completely restructure our service desk and build a new staff work room which uses space more efficiently. An interior “behind the wall” shot is below.

Since we do not have a service desk during the construction period, we are operating a service room out of Room 248 (Class of 1955 Consultation Room). We will continue to provide reserve services from this room, as well as on-call access to reference librarians.

Construction will continue over the summer, but we anticipate the room and new service desk will be open and ready for business at the start of the Fall 2015 semester. We will be posting updates on its progress.

]]>https://lippincottlibrary.wordpress.com/2015/06/13/lippincott-library-seminar-room-construction/feed/0marcellabarnhartLippincottEntrancewWallLippincottInteriorCavernScreening for Alumni-Company Linkshttps://lippincottlibrary.wordpress.com/2015/05/11/screening-for-alumni-company-links/
https://lippincottlibrary.wordpress.com/2015/05/11/screening-for-alumni-company-links/#commentsMon, 11 May 2015 20:07:32 +0000http://lippincottlibrary.wordpress.com/?p=2374Continue reading →]]>Job seekers are often interested in identifying companies that employ alumni from their schools. Here are brief descriptions of four databases that uncover alumni-company links. The databases report on different although overlapping populations, and vary in the number and type of screening variables they provide. The biographical information given typically includes contact data, employment history, and, if publicly available, compensation.

A keyword search for Wharton in the text of biographies will retrieve the names of about 1,300 individuals. You can then filter the results by country, sales, ownership or industry. Information includes contacts, compensation history, and an employment profile.

S&P Capital IQ (available in the Yablon Room at Lippincott Library)

To screen for degrees, graduation year, college/university or major:

Screening =>People=>Education

The sets created can be further refined by combining them with additional variables such as location or investment firm type (for example, the names of Wharton graduates who are hedge fund managers in New York.)

There are more than 180,000 individuals in Cap IQ identified as having an MBA. A search for MBAs graduating from Wharton retrieved more than 30,000. In addition to individual biographies, a unique feature of Capital IQ is the detailed summary that is available for the screened group of alumni. For example, the summary of the set of Wharton MBAs would consist of breakdowns and statistics of the following categories showing the number of individuals or the amount of money in each subdivision.

Geographic Locations

Industry Classifications

Company Status

Company Type

Ownership Status

Investment Firm Type

Advisory Firm Type

Market Capitalization

Total Revenue

Total Enterprise Value

EBITDA

Bloomberg (available in the Yablon Room at Lippincott Library)

Bloomberg’s PEOPLE module has biographical information on more than 2.6 million individuals. In addition to business executives, PEOPLE covers biographies of politicians, academics and celebrities. Bloomberg biographies consist of a brief career survey, address and contact information, links to news about the person’s company, and if relevant, publications, funds managed, board memberships. Compensation, if publicly available, is included.

Corporate Affiliations shows the corporate structure of more than one million public and private companies worldwide, with subsidiary listings and corporate linkage. In addition, use this database to find detailed lists of executives, their titles and biographies.

The table below shows the results of a search for women MBA graduates of the business schools ranked highest by Business Week (2014). The percentages of women in the Database is not representative of the percentage of women now receiving the MBA degree in the United States (about 45%).

]]>https://lippincottlibrary.wordpress.com/2015/05/11/screening-for-alumni-company-links/feed/0michaelhalperinHoovers menu_croppedbloomberg people variables_markedBlog Alumni Corp Affiliations advanced menuStock Price Archeologyhttps://lippincottlibrary.wordpress.com/2015/04/23/stock-price-archeology/
https://lippincottlibrary.wordpress.com/2015/04/23/stock-price-archeology/#commentsThu, 23 Apr 2015 15:39:09 +0000http://lippincottlibrary.wordpress.com/?p=2340Continue reading →]]>April often brings us a spate of income tax related questions about the price of a stock on a particular date. The questions are usually from people who want to establish the cost basis of a stock for tax purposes. Many standard financial databases can supply daily prices (high, low, close and volume) at least for the companies on the New York Stock Exchange as far back as the early 1960’s.

Table 1.

Here are the earliest dates available for daily prices of General Electric Company (GE) on several financial files.

Two specialized sources (CRSP and Global Financial Data) have some pre-1960’s stock price data as well as collateral information such as total return.

Global Financial Data is a collection of 20,000 financial and economic time series. It includes data on bonds, commodities, interest rates, stock markets and indices, futures, exchange rates, GDP, prices, and unemployment. GFD has extremely long time series, for example. U.K. Central Bank Interest Rates monthly from 1694 to date and daily from 1800 to date.

GFD’s U.S. Stock Database module has data on more than 58,000 U.S. securities from as early as 1788. About 75% of the securities are common, preferred and foreign stock, with a scattering of other issue types (e.g. ETF’s, ADRs, and Warrants). The periodicity is usually monthly before 1962, and daily after that date.

Screen by such variables as country, security type, or industry, or search for a specific company by name, ticker or other identifier. A search for the General Electric Company will bring up a default graph of GE’s stock price for the past eight quarters. Click on Download Data to bring up the following menu.

Figure 2.

Here are monthly closing prices for GE in 1893 showing the impact of the 1893 panic on the stock’s price.

Table 3.

GFD has an extensive set of graphing options for its data. Stock data can be presented adjusted for splits or for inflation, and displayed on a linear or log scale.

The graph below shows GE’s unadjusted price by month from 1893 to 1955, displaying its high close of 358 on 9/30/1929 and its low of 9.5 on 6/30/1932.

]]>https://lippincottlibrary.wordpress.com/2015/04/23/stock-price-archeology/feed/0michaelhalperinimageONE_croppedChart2_croppedBlog GE menu fixedBlog GE GFD Menu NewChart3_croppedBlog graph GE okCreate Your Own Industry-Specific League Tableshttps://lippincottlibrary.wordpress.com/2015/03/30/create-your-own-industry-specific-league-tables/
https://lippincottlibrary.wordpress.com/2015/03/30/create-your-own-industry-specific-league-tables/#commentsMon, 30 Mar 2015 18:00:05 +0000http://lippincottlibrary.wordpress.com/?p=2329Continue reading →]]>The Lippincott Library has several great resources for finding league tables. However, the majority of these pre-populated league tables are typically geared towards specific geographies and companies rather than industry-specific information. What happens if you would like to look at a league table for a specific industry? You are going to have to construct your own. Fortunately, we have a resource that will enable you to do just that. Thomson ONE, which has league tables for M&A, Equity, Bonds, and Loans, enables you to build league tables that are customized to your specifications. One great thing about the customized league tables is that, unlike the pre-populated league tables in Thomson ONE, the ones that you build yourself can pull data from a customized data range, and not just the last twelve months. Note that Thomson One only works in Internet Explorer and best in versions 7-9. See our blog post for an IE10 workaround.To start, click on Screenings & Analysis at the top of the Thomson One home screen, then click on Deals & League Tables > M&A > Advanced Search in the subsequent drop down menus. Next, check the box for “All Mergers and Acquisitions” and then click “Continue” in the bottom right-hand corner of the screen. You can customize your league table by using the filters in the menu on the left-hand side of the screen. In order to generate a league table for a specific industry or set of industries, you will need to enter the NAICS codes for the industries you want to look at. You can search within Thomson ONE or you can browse by keyword at the U.S. Census. Once you have selected your industry search criteria, continue to select additional data items to filter, such as limiting your search to deals within the last year (or the date range of your choice) by clicking on “Deal Info”>”Dates”>”Dates Effective” and selecting the relevant dates. Once you have selected your search criteria, you can create your league table by clicking “Rankings” at the bottom of the screen, and then selecting “Advisors Rank by Value” from the drop down menu. Click “Create New”, adjust your specifications as necessary, and click “Apply to Search”. Click “Execute” in the bottom right hand corner of the screen. This will generate your league table, which can be exported to Excel using the button in the top right corner. For additional information on league tables in Thomson One, see this post, A League of Your Own. For other sources for league tables, see the business FAQ and check out our blog post on Zephyr, another Library database.]]>https://lippincottlibrary.wordpress.com/2015/03/30/create-your-own-industry-specific-league-tables/feed/0wkramer2015ImageOnecroppedimage2_croppedScreenshot7_croppedimage3_croppedimage4_croppedExploring EMIS Intelligencehttps://lippincottlibrary.wordpress.com/2015/03/02/exploring-emis-intelligence/
https://lippincottlibrary.wordpress.com/2015/03/02/exploring-emis-intelligence/#commentsMon, 02 Mar 2015 14:01:11 +0000http://lippincottlibrary.wordpress.com/?p=2286Continue reading →]]>EMIS Intelligence, formerly ISI Emerging Markets, has traditionally been a great resource for exploring emerging markets. Produced by Euromoney Institutional Investor, it aggregates news, reports, statistics and company information from a wide range of providers. While the focus remains primarily on emerging markets, their recent redesign allows researchers to more easily examine world or global markets, as well as giving them the ability to find information on developed markets. While one still has the option to drill into a specific country, choosing a specific country is no longer required, making it easier to search across multiple countries and regions of interest.

The EMIS Intelligence Search page can be somewhat overwhelming because there are so many options to limit and refine your search. This example shows looking for material on armored vehicles, and limiting the results to research reports using the Publication Type filter.

Once you have run the search, you can also use the Filter options on the left-hand side of the results page to further limit by country, language and more. In the example below, two filters, Country and Publication were used to narrow search results..

Alternatively, you can use the Reports tab to explore the reports that are available. When you select the Reports tab, you will note that Analysis/Research, Ratings Analysis, News Analysis, and Analytical Commentary are automatically checked under the Publication Types list in the Filter By column.

These reports cover both developing and developed markets, and include tables that are exportable to Excel, as shown in this example of telecom data from Austria.

]]>https://lippincottlibrary.wordpress.com/2015/03/02/exploring-emis-intelligence/feed/0marcellabarnhartLoginSearch1.UsingFiltersReportsTabPubsSearchexcelRuble Regression: Exploring Correlations with Bloomberg.https://lippincottlibrary.wordpress.com/2015/02/18/ruble-regression-exploring-correlations-with-bloomberg/
https://lippincottlibrary.wordpress.com/2015/02/18/ruble-regression-exploring-correlations-with-bloomberg/#commentsWed, 18 Feb 2015 19:00:12 +0000http://lippincottlibrary.wordpress.com/?p=2292Continue reading →]]>In June 2014, the price of oil began to fall from its high of $115 a barrel. The value of the Russian Ruble, as well as the currencies of all major petroleum exporting countries began to drop along with the price of oil. Bloomberg has several correlation modules that allow us to examine the link between market variables. For example, we can quickly explore the relationship between exchange rates and oil prices using Bloomberg’s HRA program.

To plot the Russian Ruble / US Dollar exchange rate against the price of oil in Bloomberg, type: HRA <GO>

This screen shows a regression of the daily Russian Ruble Spot rate with the price of Brent Oil for the period 01/12/2014 through 01/12/2015. Two measures “R” and “R2 “ are useful for interpreting the strength of the correlation. “R” (correlation coefficient) ranges between +1 (total positive correlation) and -1 (total negative correlation). For the Russian Ruble, the R of -.97 indicates a strong negative correlation between the price of oil and the exchange rate of the Ruble against the U.S. Dollar. “R2 “ (the coefficient of determination) indicates the percentage of the change in the Ruble/U.S. Dollar (the dependent variable) that is accounted for by the change in the price of oil (the independent variable). The results of the regression can be downloaded to EXCEL.

In the table below, we show the results of regressions of national currencies for major oil exporters with the price of Brent oil for the period 01/12/2014 through 01/12/2015. China, a major oil importer, is shown as an example of a country whose currency was apparently unaffected by the drop in oil prices.

Another type of correlation program is available through the Bloomberg’s News Trends module (Type NT). NT allows charting of news story counts with historical market data. The news story counts are derived from more than 100 authoritative global sources. This is a useful way to quantify the impact of events (e.g. “Market Sell-Offs”, “Terrorist Attacks” “Epidemics”) on market data. In the graphs below we examine the relation between the appearance of the word “EBOLA” in news stories, and the daily VIX index. The VIX, often referred to as the “investor fear gauge”, is a widely used measure of market risk. There does appear to be a close relationship between the peak of the Ebola scare in October/November 2014 and the movement of the VIX. Obviously much more analysis would have to be done before concluding that the Ebola scare caused the VIX to rise.

Currency rates and oil prices are only two of the thousands of individual securities, indexes, commodities and currencies that can be used in the regression programs. For additional modules dealing with correlations, type Correlation <Help>

]]>https://lippincottlibrary.wordpress.com/2015/02/18/ruble-regression-exploring-correlations-with-bloomberg/feed/0michaelhalperinRuble regression value latestRubleTable2RubleTable1Eblola correlationCapital Cube: Not your Father’s Stock Screener.https://lippincottlibrary.wordpress.com/2015/01/23/capitalcube/
https://lippincottlibrary.wordpress.com/2015/01/23/capitalcube/#commentsFri, 23 Jan 2015 17:35:30 +0000http://lippincottlibrary.wordpress.com/?p=2269Continue reading →]]>Financial databases from Bloomberg to Yahoo Finance can screen equities based on a combination of standard financial variables and ratios, analysts’ estimates, industry and location. But if you want to identify companies with, “Aggressive Accounting Practices”, a high “Fundamental Analysis” score or possible “Sandbagging” (understated or hidden earnings) you will need a different type of stock screener. Try Capital Cube. As can be seen from the Capital Cube menu, the screening options are unusual. Capital Cube creates unique variables by taking the raw financial data from individual companies and comparing the data with averages from a group of peers. For example, a company is tagged as employing “Aggressive Accounting” when “…the company’s net income margin is higher than its peer median while the percentage of accruals is lower than peer median”. Capital Cube states that this situation is usually indicative of a company with an aggressive accounting policy. Capital Cube computes a daily “Fundamental Analysis” score for each company in its database. “The Fundamental Analysis score is calculated by comparing the company’s performance relative to peer companies across multiple attributes like relative valuation, valuation drivers, operations diagnostic, etc.”

Capital Cube uses fundamental data from the FactSet financial database. It includes more than 45,000 companies worldwide.

For additional information on equities screening see the Business FAQ:

]]>https://lippincottlibrary.wordpress.com/2015/01/23/capitalcube/feed/0michaelhalperinCapital Cube MenuCapital Cube graphClean Energy by the Numbers: Data Sourceshttps://lippincottlibrary.wordpress.com/2015/01/14/cleanenergydata/
https://lippincottlibrary.wordpress.com/2015/01/14/cleanenergydata/#commentsWed, 14 Jan 2015 17:00:54 +0000http://lippincottlibrary.wordpress.com/?p=2243Continue reading →]]>According to Christiana Figueres, Executive Secretary of the UN Climate Convention, “Never before have the risks of climate change been so obvious and the impacts so visible.” We could add that never before has there been such an interest in sources of information for climate change, energy use and “clean” (non-polluting) technology.

The IEA is an autonomous organization that works to ensure access to reliable, affordable and clean energy for its 29 member countries and beyond. Data is available on coal, oil, natural gas, electricity and renewables.

Bloomberg BI

The Bloomberg Industries module includes Climate Change as a sector. Here you will find news, analysis, and impacts by different industries. Type: BI CLIM . Data is available on macroeconomics, industries, companies, thematics, and Green Bank Ratings.

The World Resources Institute provides data and infographics on Climate Change and Clean Tech. WRI decribes itself as a “…global research organization that turns big ideas into action at the nexus of environment, economic opportunity and human well-being.” One project is the U.S. Climate Action Plan. Extensive data is available on a number of topics including indicators of sustainable agriculture, country clean tech data, and country GHG emissions, as shown in the graph below.

Business and economic forecasts that are past their shelf life, such as GDP forecasts for the year 2010 made in the year 2008, might seem to be of little value. But business researchers examine old forecasts to test their accuracy or to better understand the economic climate of a period. It is well known that forecasters almost universally missed predicting the “Great Recession” business decline of 2008/2009. For example, The Economist’s Poll of Forecasters for Jan 12, 2008 (pg. 89) predicted that U.S. GDP would increase 1.8% in 2008 and 2.6% in 2009. GDP actually fell slightly in 2008 and was down 2.8% in 2009.

Here are some sources of historical forecasts that will let you exercise 20/20 hindsight.

TheEconomist Historical Archivehas monthly macroeconomics projections for major industrialized countries. The series was introduced in the August 18, 1990 issue, and gives a consistent source for the projections of three macroeconomic variables from 1991 to 2011. Each month, the Economist gives the averages of the one year forecasts of international forecasters for GDP, the Consumer Price Index, and the Current Account Balance (as a percentage of GDP). The numbers are given as percentage changes.

To retrieve the entire series of monthly projections, search for:

Poll of Forecasters OR Economic Forecasts (in title)

Limit publication date to AFTER 1989.

To see a PDF of the tables, click on View Page and then on Economic Forecasts.

Forecasts from 1990 – 2003 have the option of being exported to a spreadsheet (example below from the Oct 9th 1999 Economist)

Economist Projections from Oct 9 1999

Archived reports from Business Monitor International (BMI) give projections for the economies of major countries, and in addition, supply country industry forecasts. BMI covers some 100 countries and 25 industry groups. Not all industries are available for all countries, but their coverage is impressive. For example, BMI has archived reports of the Serbian Auto Industry from 2006 on.

From the BMI main menu:

Advanced Search => Reports & Strategic Content =>Reports Archive

For general business and economic forecasts, search for the report title with the name of the country – for example:

Two general business databases,Business Source Complete and ABI/Inform, contain several full-text publications devoted to business and economic forecasts. Search their publication files for the word Forecast* anywhere in the title.

Sean Griffin from Euromonitor’s Passport GMID Database recently sent us a bulletin celebrating the Great American Smokeout. This is an annual event sponsored by the American Cancer Society designed to encourage people to quit smoking for 24 hours with the hope that the decision will be permanent. Sean uses the Passport database to examine smoking habits in the U.S. With his permission, we’ve adopted his examples and descriptions in the following post.

Smoking Habits

Smoking was much more accepted in the past. For example, RJ Reynolds was a sponsor of The Flintstones in the early 1960’s. Fred and Barney Rubble became spokestoons for Winston Cigarettes. RJ Reynolds also went on to introduce the Joe Camel mascot to promote Camel cigarettes. RJ Reynolds retired Joe Camel in 1997 after the campaign was criticized for influencing children to smoke,

Attitudes towards smoking have certainly changed over the years. The consumer lifestyles report for the US in Passport reveals that the smoking prevalence in the US has declined in recent years. In addition to health concerns, recent smoking restrictions have contributed to the decline of smoking rates. Another factor contributing to the decline is the rising demand for electronic or e-cigarettes. The datasets taken from Passport below indicate that the historic decline in smoking is expected to continue.

Market Sizes – Forecast Growth of Cigarettes

The Passport database gives a global view of the cigarette market, and forecasts a market decline in most major economies.

The US market, for example, has a projected compound annual growth rate (CAGR) of -2.3% for the period of 2013-18.

To access these tables, Click on SEARCH, and from the Category Tree, scroll down to